Today, as represented by such a term as big data, there is a flood of data. How to analyze and handle the huge amounts of data is a social scientific problem of the highest importance in future information science. Big data typically result from some phenomena. Thus, analysis of big data often corresponds to a certain type of inverse problem for searching a cause from a result. A computer is configured to routinely perform regular processing, and simply performs calculation on the basis of an algorithm when an initial value is given. In general, however, there is no efficient algorithm for such a problem of obtaining an initial value from a result, and an exhaustive search has to be conducted for finding the initial value in the worst case. A computer capable of efficiently solving a problem that requires an exhaustive search would therefore be very useful.
Quantum computers are highly expected to be suitable for exhaustive search problems. A quantum computer is constituted by basic elements called qubits, which can be “0” and “1” at the same time. Computation using all candidates of a solution simultaneously as initial values is thus possible, which provides just the possibility for an exhaustive search. However, a quantum computer needs to maintain quantum coherence over the entire computation time, but there are no prospects therefor.
A technique called adiabatic quantum computing (AQC) has been drawing attention under such circumstances (NPL 1). This method consists of setting a Hamiltonian H^p so that the solution of a problem is a ground state of a system, setting another Hamiltonian H^0 whose ground state is clarified and readily provided, preparing the ground state of H^0 in a computation system first, and changing Hamiltonian H^0 to Hamiltonian H^p spending sufficiently long time. A sufficiently slow change allows the system to keep staying in its ground state, which is the principle how to obtain a solution in the adiabatic quantum computing. The computation principle as described above can be described by the Schrodinger equation of Eq. (1) using the Hamiltonian of Eq. (2) where the computation time is represented by τ.
                              i          ⁢                                          ⁢          ℏ          ⁢                                    ∂                                                                                  ∂              t                                ⁢                                                ψ              ⁡                              (                t                )                                      〉                          =                                            H              ^                        ⁡                          (              t              )                                ⁢                                                ψ              ⁡                              (                t                )                                      〉                                              [                  Eq          .                                          ⁢          1                ]                                                      H            ^                    ⁡                      (            t            )                          =                                            (                              1                -                                  t                  τ                                            )                        ⁢                                          H                ^                            0                                +                                    t              τ                        ⁢                                          H                ^                            p                                                          [                  Eq          .                                          ⁢          2                ]            
The adiabatic quantum computing is also applicable to problems requiring an exhaustive search, and reaches a solution through a one-way process. If, however, a computational process needs to obey the Schrodinger equation of Eq. (1), the quantum coherence needs to be maintained as similar to quantum computing. Note, however, that the adiabatic quantum computing makes the whole qubit system interact at the same time while quantum computing repeats gate operation on one qubit or between two qubits, and the difference leads to different concepts of coherence. Let us assume a gate operation on a qubit, for example. If there is interaction between this qubit and another qubit in the operation, this will be a cause of decoherence; however, in the adiabatic quantum computing, since all qubits are made to interact at the same time, the case of this example does not correspond to decoherence. In light of this difference, the adiabatic quantum computing is considered to be more robust against decoherence than quantum computing is.
The adiabatic quantum computing, however, also has disadvantages. Even with higher robustness against decoherence than quantum computing, sufficient coherence is still required if the computation process obeys the Schrodinger equation of Eq. (1). In addition, the fact that the system that can achieve the adiabatic quantum computing is a superconducting magnetic flux qubit system is also a disadvantage (PTL 1, NPL 2). This is because use of superconducting requires cryogenic cooling equipment. The requirement of very low temperature is disadvantageous in achieving a practical computer.